49 research outputs found

    The U.S. Science and Technology Workforce

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    [Excerpt] In the 21st century, global competition and rapid advances in science and technology will challenge the scientific and technical proficiency of the U.S. workforce. Policymakers often discuss policy actions that could enhance the nation’s science and technology (S&T) workforce— deemed by some as essential to both meet U.S. workforce demands as well as to generate the new ideas that lead to improved and new industries that create jobs. The America COMPETES Act (P.L. 110-69) addresses concerns regarding the S&T workforce and STEM education, and the 111th Congress is debating funding for the programs authorized within it. Policymaker discussions tend to focus on three issues: demographic trends and the future S&T talent pool, the current S&T workforce and changing workforce needs, and the influence of foreign S&T students and workers on the U.S. S&T workforce. Many perspectives exist, however, on the supply and demand of scientists and engineers. Some question the fundamental premise that any action is necessary at all regarding U.S. competitiveness. They question whether or not the S&T workforce and STEM education are problems at all. The first issue of demographic trends and the future S&T talent pool revolves around whether the quality of science, technology, engineering and mathematics (STEM) education received by all Americans at the pre-college level is of sufficient quality that workers are available to satisfy current and future workforce needs. In response, some policymakers propose taking actions to increase the number of Americans interested in the S&T workforce. These policies are motivated by demographic trends that indicate the pool of future workers will be far more diverse than the current STEM workforce. Proposed policies would take actions to enhance the quality of STEM education these Americans receive so they are able to consider S&T careers, and to recruit them into the S&T workforce. The second issue regarding the current S&T workforce and changing workforce needs tend to focus on whether or not the number of Americans pursuing post-secondary STEM degrees is sufficient to meet future workforce needs compared to students in countries considered to be U.S. competitors. The goal of proposed policies responding to this concern to reinvigorate and retrain Americans currently trained in science and engineering who voluntarily or involuntarily are no longer part of the current STEM workforce. The third issue focuses on whether or not the presence of foreign S&T students and workers is necessary to meet the nation’s workforce needs and attract the best and brightest to bring their ideas to the United States, or if the presence of such individuals adversely affects the U.S. S&T students and workers. Policy discussions focus on immigration policy, primarily increasing the ability of foreign STEM students currently in U.S. universities to more easily obtain permanent admission, and increasing the number of temporary worker visas available so more talent from abroad can be recruited to the United States. The challenge facing policymakers when making decisions regarding the S&T workforce is that science, engineering, and economic conditions are constantly changing, both in terms of workforce needs as well as the skills the STEM workforce needs to be marketable relative to demand

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
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